An Analytical Approach Differentiates Between Individual and Collective Cancer Invasion

Tumour cells employ a variety of mechanisms to invade their environment and to form metastases. An important property is the ability of tumour cells to transition between individual cell invasive mode and collective mode. The switch from collective to individual cell invasion in the breast was shown...

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Main Authors: Elad Katz, Wim Verleyen, Colin G. Blackmore, Michael Edward, V. Anne Smith, David J. Harrison
Format: Article
Language:English
Published: Wiley 2011-01-01
Series:Analytical Cellular Pathology
Online Access:http://dx.doi.org/10.3233/ACP-2011-0003
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author Elad Katz
Wim Verleyen
Colin G. Blackmore
Michael Edward
V. Anne Smith
David J. Harrison
author_facet Elad Katz
Wim Verleyen
Colin G. Blackmore
Michael Edward
V. Anne Smith
David J. Harrison
author_sort Elad Katz
collection DOAJ
description Tumour cells employ a variety of mechanisms to invade their environment and to form metastases. An important property is the ability of tumour cells to transition between individual cell invasive mode and collective mode. The switch from collective to individual cell invasion in the breast was shown recently to determine site of subsequent metastasis. Previous studies have suggested a range of invasion modes from single cells to large clusters. Here, we use a novel image analysis method to quantify and categorise invasion. We have developed a process using automated imaging for data collection, unsupervised morphological examination of breast cancer invasion using cognition network technology (CNT) to determine how many patterns of invasion can be reliably discriminated. We used Bayesian network analysis to probabilistically connect morphological variables and therefore determine that two categories of invasion are clearly distinct from one another. The Bayesian network separated individual and collective invading cell groups based on the morphological measurements, with the level of cell-cell contact the most discriminating morphological feature. Smaller invading groups were typified by smoother cellular surfaces than those invading collectively in larger groups. Interestingly, elongation was evident in all invading cell groups and was not a specific feature of single cell invasion as a surrogate of epithelial-mesenchymal transition. In conclusion, the combination of cognition network technology and Bayesian network analysis provides an insight into morphological variables associated with transition of cancer cells between invasion modes. We show that only two morphologically distinct modes of invasion exist.
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spelling doaj-art-1a7744aed2d44623b6e08c188a0e2ae42025-02-03T00:59:39ZengWileyAnalytical Cellular Pathology2210-71772210-71852011-01-01341-2354810.3233/ACP-2011-0003An Analytical Approach Differentiates Between Individual and Collective Cancer InvasionElad Katz0Wim Verleyen1Colin G. Blackmore2Michael Edward3V. Anne Smith4David J. Harrison5Breakthrough Research Unit and Division of Pathology, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UKSchool of Biology, University of St Andrews, St Andrews, UKDefiniens AG, Munich, GermanyFaculty of Medicine, Section of Dermatology, Division of Cancer Sciences, University of Glasgow, Glasgow, UKSchool of Biology, University of St Andrews, St Andrews, UKBreakthrough Research Unit and Division of Pathology, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UKTumour cells employ a variety of mechanisms to invade their environment and to form metastases. An important property is the ability of tumour cells to transition between individual cell invasive mode and collective mode. The switch from collective to individual cell invasion in the breast was shown recently to determine site of subsequent metastasis. Previous studies have suggested a range of invasion modes from single cells to large clusters. Here, we use a novel image analysis method to quantify and categorise invasion. We have developed a process using automated imaging for data collection, unsupervised morphological examination of breast cancer invasion using cognition network technology (CNT) to determine how many patterns of invasion can be reliably discriminated. We used Bayesian network analysis to probabilistically connect morphological variables and therefore determine that two categories of invasion are clearly distinct from one another. The Bayesian network separated individual and collective invading cell groups based on the morphological measurements, with the level of cell-cell contact the most discriminating morphological feature. Smaller invading groups were typified by smoother cellular surfaces than those invading collectively in larger groups. Interestingly, elongation was evident in all invading cell groups and was not a specific feature of single cell invasion as a surrogate of epithelial-mesenchymal transition. In conclusion, the combination of cognition network technology and Bayesian network analysis provides an insight into morphological variables associated with transition of cancer cells between invasion modes. We show that only two morphologically distinct modes of invasion exist.http://dx.doi.org/10.3233/ACP-2011-0003
spellingShingle Elad Katz
Wim Verleyen
Colin G. Blackmore
Michael Edward
V. Anne Smith
David J. Harrison
An Analytical Approach Differentiates Between Individual and Collective Cancer Invasion
Analytical Cellular Pathology
title An Analytical Approach Differentiates Between Individual and Collective Cancer Invasion
title_full An Analytical Approach Differentiates Between Individual and Collective Cancer Invasion
title_fullStr An Analytical Approach Differentiates Between Individual and Collective Cancer Invasion
title_full_unstemmed An Analytical Approach Differentiates Between Individual and Collective Cancer Invasion
title_short An Analytical Approach Differentiates Between Individual and Collective Cancer Invasion
title_sort analytical approach differentiates between individual and collective cancer invasion
url http://dx.doi.org/10.3233/ACP-2011-0003
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